code: def test_transform(pd_es, dask_es):
      pytest.skip(
          "TODO: Dask issue with `series.eq`. Fix once Dask Issue #7957 is closed.",
      )
      primitives = list_primitives()
      trans_list = primitives[primitives["type"] == "transform"][
          "name"
      ].tolist()
      trans_primitives = [
          prim for prim in trans_list if prim not in UNSUPPORTED
      ]
      agg_primitives = []
      cutoff_time = pd.Timestamp("2019-01-05 04:00")
  
      assert pd_es == dask_es
  
      # Run DFS using each dataframe as a target and confirm results match
      for df in pd_es.dataframes:
          features = dfs(
              entityset=pd_es,
              target_dataframe_name=df.ww.name,
              trans_primitives=trans_primitives,
              agg_primitives=agg_primitives,
              max_depth=2,
              features_only=True,
          )
  
          dask_features = dfs(
              entityset=dask_es,
              target_dataframe_name=df.ww.name,
              trans_primitives=trans_primitives,
              agg_primitives=agg_primitives,
              max_depth=2,
              features_only=True,
          )
          assert features == dask_features
  
          # Calculate feature matrix values to confirm output is the same between dask and pandas.
          # Not testing on all returned features due to long run times.
          fm = calculate_feature_matrix(
              features=features[:100],
              entityset=pd_es,
              cutoff_time=cutoff_time,
          )
          dask_fm = calculate_feature_matrix(
              features=dask_features[:100],
              entityset=dask_es,
              cutoff_time=cutoff_time,
          )
  
          # Categorical categories can be ordered differently, this makes sure they are the same
          dask_fm = dask_fm.astype(fm.dtypes)
  
          # Use the same columns and make sure both indexes are sorted the same
          dask_computed_fm = (
              dask_fm.compute()
              .set_index(df.ww.index)
              .loc[fm.index][fm.columns]
          )
          pd.testing.assert_frame_equal(fm, dask_computed_fm)
  
file_path: featuretools/featuretools/tests/primitive_tests/test_dask_primitives.py
imports: import pandas
  import pytest
  from featuretools import calculate_feature_matrix, dfs, list_primitives
  from featuretools.feature_base.cache import feature_cache
  from featuretools.primitives import get_aggregation_primitives, get_transform_primitives
  from featuretools.tests.testing_utils import to_pandas
  from featuretools.utils.gen_utils import Library
label_desc: Use image node_id 2 for calling a global function with example usage: test_transform(pd_es, dask_es) without return types